My forecast is flawed in its simplicity and forecasts a jump in vacancy of 6.1% by the first quarter of 2009. The structure of leases and dynamics of the office markets prevent that rapid an increase. What is useful about this model is its ability to quantify the pressures on Occupancy. Does it make sense though? Many argue that Consumer Confidence moves in a similar pattern as other predictive indicators and when used in a model creates a false degree of accuracy by simply parroting those other variables.[1] I have avoided this problem however, by using no other variables. I am not claiming that reductions in Consumer Confidence cause increases in office vacancies.  However, like most forward looking indicators, factors which result in changes to Consumer Confidence appear also to result in subsequent changes to office vacancies.


Consumer Confidence is an excellent measurement of the mood of the American public.  The importance of understanding the general population can be easily seen in examples such as the initial battle between the Mac and PC. The PC beat out a technically superior rival by catering to those features which the majority valued including price, availability of software, and compatibility. This pattern is the same in nearly every industry and field. If you can understand the mood of the herd, you have a better chance of winning.


So coming back to Commercial Real Estate (CRE), the herd is important here too. Certainly CRE decisions are not made by the common citizen. With assets often valued in the billions of dollars, development cycles lasting two to twenty years, and regulations requiring teams of talented lawyers and accountants, CRE is not a field for the inexperienced. And yet, the herd controls all. When reviewing the decisions made for investing, leasing, underwriting, or building in CRE, it all comes back to the income producing power of a property. That income power is beholden to its utility. That utility is ultimately judged by the herd. Build a mall where no one goes, or an office that no one wants to work in, or a hotel that no one will visit, and you are done. Own in an economy where once successful patterns change or stop altogether and face the same result. To win in the personal computer game, navigate to the front of the herd.

To win in CRE, accurately predict pricing and act on your predictions.

The commonly heard excuse for poor decisions is that 'this property is different.' It is true that a fundamental component of real property is that each is unique. No two properties occupy the same physical space, and are therefore truly different from every other property. Equally true is that some properties outperform others. But what is also true is that all properties are influenced by the same external forces. Those external forces are economic.


The economy is often measured in terms of GDP growth. GDP is made up of private consumption, investments, net exports, and government expenditures. Of these, roughly 70% is private consumption. Put another way, the herd controls the majority of the economic growth, or decline. The best measure for the attitude of the herd, and therefore its propensity to increase or decrease consumption, is consumer confidence. That would explain why consumer confidence is so closely linked to office vacancies. As consumer consumption increases, so do the payrolls. And of course, increasing payrolls means increasing employment which means increasing demand for office space. The same goes for declining demand. Declining consumer sentiment leads to declining demand for CRE. But how quickly, and for how long?


[1]  An excellent article on the viability of Consumer Confidence was published in May/June 1991 by Alan Garner in The Economic Review released by the Federal Reserve Bank of Kansas City.



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